Vehicle Sensor Self-Calibration for In-Drive Fault Detection
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Solution Overview
Problem
Autonomous vehicles face challenges in detecting and responding to faulty sensors while in operation, as existing methods require manual intervention and may not efficiently identify sensors that have moved or become inoperative, posing risks to the vehicle and its surroundings.
Innovation Solution
A system that includes a processor and sensors, capable of performing self-calibration routines to determine calibration parameter values, automatically detecting if sensors have moved or become inoperative by comparing these values with predetermined acceptable ranges, and initiating remedial actions while the vehicle is in motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to detect faulty sensors, then detection accuracy can be maintained, but response time is delayed and operational efficiency decreases
Solution Approach 1:
The system performs self-diagnosis by automatically monitoring sensor data quality and detecting faults without external intervention. The processor continuously evaluates sensor outputs against expected parameters and autonomously identifies when sensors become inoperative or misplaced, enabling the vehicle to self-correct and maintain operational reliability.
Solution Approach 2:
The system implements continuous feedback loops where sensor data is constantly monitored and compared against calibration parameters. When deviations indicate sensor faults, the system provides immediate feedback to the control processor, which then adjusts vehicle operations or triggers alerts, creating a closed-loop detection and response mechanism.
2Reliability
If continuous monitoring of all sensors is performed, then detection reliability is improved, but computational load and energy consumption increase
Solution Approach 1:
The system monitors sensor data at different levels of intensity based on operational context. During normal operation, monitoring occurs at a reduced level, while during critical maneuvers or when anomalies are detected, the system intensifies monitoring of specific sensors. This partial monitoring approach maintains detection reliability while reducing overall computational load and energy consumption.
Solution Approach 2:
The system applies different monitoring strategies to different sensors based on their criticality and current performance. When a sensor shows signs of degradation, the system increases monitoring focus on that specific sensor rather than uniformly increasing monitoring across all sensors, optimizing energy usage while maintaining detection reliability.
3Measurement precision
If sensor calibration is performed frequently, then measurement precision is maintained, but vehicle operation time is reduced due to calibration interruptions
Solution Approach 1:
The system performs calibration checks at predetermined intervals and proactively identifies sensors that are approaching calibration thresholds before they become faulty. By detecting degradation trends early, the system can schedule calibration during planned maintenance windows rather than interrupting operations when sensors fail, maintaining measurement precision while maximizing continuous operation time.
Solution Approach 2:
The calibration schedule is dynamic rather than static. The system adjusts calibration frequency based on actual sensor performance, environmental conditions, and operational intensity. Sensors showing stable performance undergo less frequent calibration, while those in demanding conditions or showing drift are calibrated more often, optimizing the balance between measurement precision and operational continuity.
Data Source
AI summary
In an embodiment, a processor is configured to perform, while a vehicle is driving in an uncontrolled environment, a self-calibration routine for each sensor from the plurality of sensors to determine at least one calibration parameter value associated with that sensor. The processor is further configured to determine, while the vehicle is driving in the uncontrolled environment, and automatically in response to performing the self-calibration routine, that at least one sensor from the plurality of sensors has moved and/or is inoperative based on the at least one calibration parameter value associated with the at least one sensor being outside a predetermined acceptable range. The processor is further configured to perform, in response to determining that at least one sensor from the plurality of sensors has moved and/or is inoperative, at least one remedial action at the vehicle while the vehicle is driving in the uncontrolled environment.